Investors

NOMYO AI is building the infrastructure layer for real intelligence – systems that reason, plan, and act. We are seed-stage, revenue-positive, and ready to scale.

The Opportunity

GenAI’s first wave is losing momentum. Transformer-only models hit diminishing returns on both adoption and monetization. The market needs a different architecture.

Metric	Value
GenAI TAM (economic value)	$3.5 trillion (McKinsey 2025)
GenAI spend (2025)	$400 billion (Deloitte)
Knowledge workers globally	1 billion (Gartner 2025)
Year 5 ARR target	$75 million
Long-term upside	$6 billion ARR at 3M monthly users

The Problem: An Industry Trade-Off

Today’s AI forces a choice between adoption and monetization – and you can only pick one.

	High Adoption / Low Monetization	High Monetization / Low Adoption
Consumer AI	Individuals automate low-value tasks. Value capped at efficiency gains.
Enterprise AI		Only organizations with pre-engineered systems extract real value. Most struggle with real-world complexity.

The truth: When revenue is the goal, adoption and monetization don’t sum – they multiply.

ARR ~ MAU x ARPU

Our insight: NOMYO turns this trade-off into a value ladder. Users start with high-adoption, low-cost interactions and are pulled toward high-value, high-monetization workflows over time.

The math: 3% of Anthropic’s MAU x 3% of Symphony’s ARPU = 70% of OpenAI’s revenue.

The Solution: Biology-Inspired AGI

NOMYO’s platform doesn’t predict next tokens. It builds persistent models of users’ worlds, learns from every interaction, and orchestrates specialized agents toward real outcomes.

Three pillars:

1. skandha – AGI platform with dynamic knowledge graphs, multi-level agent hierarchy, and embedding-enabled graph databases
2. nomyo SDK – End-to-end encrypted inference client with AES-256-GCM + RSA-4096 OAEP security
3. nomyo-router – Open source inference router with semantic caching and model deployment-aware routing

Real intelligence doesn’t chat. It builds.

Revenue Model: Three Tiers, One Ladder

Live today: self-serve subscriptions for the e2ee encrypted-inference product – Professional at $199/month (all security tiers included), Enterprise custom-priced.

Planned: the consumer ladder below – chat.nomyo.ai (the Assistant) pricing – into which enterprise engagements upsell. Every tier is designed to upsell to the next; users enter at Basic and graduate to Pro, then Enterprise.

	Basic	Pro	Enterprise
Monthly fee	$20	$125	$200 / user
Core product	Limited	Full	Full
Team features	–	–	Shared workflows, knowledge graph
Governance	Individual	Individual	Org-wide isolation
Admin & support	–	Standard	SSO, audit, RBAC, SLA
Add-ons	–	–	Encrypted inference (also available standalone as a live subscription, see above), consulting

Traction

• Live platform – encrypted-inference stack operational and deployed in customer engagements
• Revenue positive – bootstrapped, sustainable, no burn
• Paying customers – delivery engagements and live self-serve encrypted-inference subscriptions
• Open source contributions (nomyo-router)
• Defensible business model built on biology-inspired architecture

The Moat

Incumbents are locked in. Their sunk costs in Transformer-only stacks – server farms, personnel, branding – make it nearly impossible to pivot. They can’t declare their core approach wrong.

Others are coming. This is an arms race, not winner-take-all. But we are years ahead in the areas that matter: persistent memory, goal-oriented orchestration, dynamic knowledge graphs, and reinforcement learning at the system level.

The differences are qualitative, not quantitative. And they compound.

• Persistent Affordance Graph – builds a living model of each user’s world
• Bio-inspired architecture – catabolic (active) and anabolic (dreaming/consolidating) modes
• Combinatorial bandit RL – explores workflow space, exploits known value paths
• e2ee inference – GDPR-compliant, running exclusively on models we host in our own German facility
• Encrypted inference reduces dependency on expensive external model calls

The Team

alpha nerd – Co-Founder

C-level executive with 30+ years in software development, architecture, and martech. Serial entrepreneur with two successful exits. Deep expertise in EU data privacy and GDPR compliance.

Holly Wood – Co-Founder

10 years leading AI and computational neuroscience R&D. Princeton undergraduate, UC Berkeley Law. US patent holder for algorithmic unsupervised learning. Guest lecturer at UC Berkeley’s Sutardja Center and Stanford Neurodiversity Project.

Contact

For investment inquiries, please reach out to us directly.